Diabetic Retinopathy Is a Predictor of Progression of Diabetic Kidney Disease: A Systematic Review and Meta-Analysis

Methods A systematic search was conducted on PubMed, Embase, and the Google scholar for eligible studies through September 2021. The quality of selected articles was assessed using JBI checklist. Higgins and Thompson's I2 statistic was used to see the degree of heterogeneity. Based on degree of heterogeneity, fixed or random effects model was used to estimate pooled effect using inverse variance method. Results were expressed as hazard ratios and odds ratios with 95% CIs. Results After scrutinizing 18017 articles, data from ten relevant studies (seven prospective and three retrospective) was extracted. DR was significantly associated with DKD progression with a pooled HR of 2.42 (95% CI: 1.70–3.45) and a pooled OR of 2.62 (95% CI: 1.76–3.89). There was also a significant association between the severity of DR and risk of progression of DKD with a pooled OR of 2.13 (95% CI: 1.82–2.50) for nonproliferative DR and 2.56 (95% CI: 2.93–.33) for proliferative DR. Conclusion Our study suggests that presence of DR is a strong predictor of risk of kidney disease progression in DKD patients. Furthermore, the risk of DKD progression increases with DR severity. Screening for retinal vascular changes could potentially help in prognostication and risk-stratification of patients with DKD.


Introduction
e global burden of diabetes mellitus (DM) has been steadily rising over the past few decades. e International Diabetes Federation (IDF) predicts an increase in the number of patients with diabetes to 643 million by 2030 and to 784 million by 2045 [1]. An estimated 30-50% of patients with diabetes will develop DKD during their lifetime [2]. DKD is, at present, the leading cause of end-stage kidney disease (ESKD) worldwide and causes significant morbidity, mortality, and healthcare burden [3,4]. Indeed, much of the cardiovascular death in diabetes appears to be closely related to the development of kidney disease [5,6]. e prediction of DKD progression in patients with type 1 and type 2 DM represents an important clinical and public policy challenge.
DKD is often not recognized in the initial stages due to lack of routine screening for microalbuminuria, especially in low-resource settings. Clinicians are heavily reliant on serum creatinine and urine dipstick, both of which are flawed screening tools, and there is a paucity of validated biomarkers that can help in early detection of chronic kidney disease (CKD) [7]. ere is also considerable heterogeneity in the natural history of DKD which makes staging and prognostication challenging. While some patients progress through the classically described five stages of diabetic nephropathy (DN), some with microalbuminuria regress to normoalbuminuria and do not progress, whereas some normoalbuminuric patients develop progressive renal function decline, without a preceding microalbuminuria stage [8][9][10][11][12].
us, early recognition of those at risk of progression to ESKD is the need of the hour to enable timely initiation of nephroprotective therapies to prevent or slow worsening of kidney disease and thereby attenuate DKDassociated mortality and healthcare burden.
DR is one of the microvascular complications in diabetes and approximately affects about 30% of patients with diabetes [13]. ere is remarkable homology between the eye and the kidney in terms of developmental, structural, and pathophysiological pathways and it is, therefore, rather unsurprising that DKD is often closely associated with DR [14]. In patients with diabetes, glycemic and blood pressure control reduces the incidence and progression of both DR and DKD, suggesting a common pathogenesis of these two complications [15][16][17][18][19][20][21].
Clinically, DR is screened with fundoscopy, which is a relatively noninvasive, inexpensive method [22,23]. It can be routinely performed during outpatient screening for chronic complications of diabetes. e presence of established DR strongly suggests DKD as the cause of kidney disease in a diabetes patient with renal dysfunction and epidemiological studies have found that DR may be a good screening tool for recognition of DN [24][25][26][27][28][29][30]. However, the role of DR as a predictor of progression to ESKD has not been clearly elucidated. us, in this systematic review and meta-analysis, we sought to pool data from available studies and obtain a more reliable estimate of the effect of DR on the risk of progression of DKD in patients with DM.

Search Strategy.
A systematic search of PubMed, Embase, and Google Scholar was performed by two independent reviewers (M.G. and T.C.B.) for articles studying the association between DR and progression of DKD in September 2021. Using MeSH terms as well as the free words, the search strategy included the following: [((diabetic retinopathy stage OR retinopathy stage) AND (risk factor OR prognostic factor OR predict OR etiology) AND (nephropathy stage OR diabetic nephropathy stage OR DKD stage) AND (diabetic nephropathy progression OR nephropathy progression)]. e last search date was September 30, 2021.

Selection Criteria.
e inclusion criteria for articles were as follows: (1) longitudinal studies (prospective and retrospective); (2) studies including patients with DM (irrespective of type of DM) and presumed or biopsy-proven DKD; (3) presence of DR defined according to well-validated scales, such as the Early Treatment Diabetic Retinopathy Study severity scale; and (4) studies reporting progression of DKD. Studies with no full text, cross-sectional design, and insufficient data to compute hazards ratio (HR) (or odds ratio) for DKD progression were excluded. e rigorous eligibility criteria were strictly followed by two independent reviewers (M.G. and T.C.B.) to control for publication bias. Any disagreements in the inclusion of a paper were resolved by a third researcher (I.R.R.).

Data Extraction and Quality Assessment.
Using standardized forms, data on year of publication, first author's name, country where study was undertaken, study setting, follow-up periods, sample size, definitions of the exposure (DR) and outcome (ESKD), baseline demographic data including average age of the participants, duration of diabetes, average blood pressure, HbA1c, average eGFR values, and the reported effect estimates (HR or OR with 95% CIs) were extracted from the eligible studies.
e Joanna Briggs Institute (JBI) critical appraisal checklist for cohort studies was used to assess the quality of the selected articles [31]. e tool contains eleven items. e evaluation scores ranged from 0 to 11, with <3 defined as "low quality," 3-6 as "moderate quality," and >6 as "high quality." e JBI quality scores of included articles are provided in Table 1.

Data Synthesis and Analysis.
Results were expressed as hazard ratios and odds ratios with 95% CIs. e degree of between-study heterogeneity was estimated using the Higgins and ompson's I 2 statistic, with I 2 of >75% indicating considerable heterogeneity. Pooled effect estimates for DR and DKD progression, as well as for DR severity and risk of DKD progression, were computed using the inverse variance method. A fixed effects model was used when between-study heterogeneity was low, while a random effects model was used if heterogeneity was high. A sensitivity analysis was performed to ascertain robustness of the obtained results. To ascertain publication bias, a funnel plot was constructed by plotting the standard errors of the studies against the corresponding HR. All analyses were performed using R version 4.1.1.

Literature Search Results.
A total of 18,275 articles were identified after a rigorous search on PubMed, Embase, and Google Scholar. Out of these 18,275 articles, 258 articles were identified as duplicates. e remaining 18017 articles were screened based on the abstracts and titles, separately, by two independent reviewers. Any disagreements on the inclusion of a paper were resolved by the third researcher. A full-text assessment was conducted and finally 10 articles were included in the meta-analysis. e article selection process has been summarized in Figure 1.

Study Characteristics.
e relevant characteristics of the selected publications are summarized in Tables 1 and 2. A total of 14,355 patients across the 10 studies are included. All included studies were judged to be of high quality, with a score of seven or more as per the JBI checklist.

DR and DKD Progression.
Of the ten studies, six reported results using both HR and OR, two reported HR alone, and two reported OR alone. erefore, results were analysed, and pooled estimates were computed as HR and OR both, separately. Since the I 2 statistic indicated International Journal of Nephrology 3 International Journal of Nephrology

Discussion
is systematic review included ten longitudinal studies with a pooled sample size of 14,355. Meta-analysis of data from the included studies found that the presence of DR was significantly associated with DKD progression, with a pooled hazard ratio of 2.42 (95% CI: 1.70-3.45). e obtained results were consistent even when pooled estimates were reported in terms of odds ratio (OR 2.62, 95% CI:1.76-3.89). Sensitivity analysis excluding studies with presumed DKD (rather than biopsy-proven cases) and that excluding retrospective studies also yielded similar results, indicating robustness of our findings. All the included studies in our review found a significant association between DR and ESKD, except the one by Mottl et al. [35]. ere are two possible factors that may explain the lack of association in the Mottl et al. study. Firstly, patients with serum creatinine of >1.5 mg/dL were excluded from this study. Hence, very few patients (<2.5%) developed ESKD during the study period and this low event rate may have influenced the results. Secondly, patients were grouped as having no/mild DR versus moderate/severe DR, rather than as having no DR versus having DR. It is important to note that this study did find that DR was associated with a nearly twofold increase in risk of doubling of serum creatinine and an increase in incident macroalbuminuria.
Furthermore, we found that the severity of DR was also significantly associated with DKD progression. ere was an increase in DKD progression risk as severity of DR increased, with a pooled OR of 2.13 (95% CI:      venular widening was a predictor of risk of CKD [23,42]. Lee et al. evaluated retinal perfusion status in patients with diabetes using fluorescein angiography and found that nonperfusion of more than ten-disc areas was associated with a sixfold risk of CKD progression [43]. While the association of DR and presence of DKD is already clearly established, it is unclear whether presence of DR (and its severity) is also associated with DKD progression and our study specifically answers this question. Given the unpredictable natural course of DKD, the ability to identify patients at high risk of progression of DKD using DR findings would be an invaluable clinical tool and could potentially guide the nephrologist to individualize therapies tailored to an individual's future risk of ESKD. Tests to ascertain presence (and severity) of DR are noninvasive and economical, thereby making implementation of routine DR screening practicable.
A recent meta-analysis by Guo et al. found an association between DR and incidence of cardiovascular (CV) disease and CV mortality in patients with diabetes [44]. erefore, a fundus examination in a patient with diabetes is necessary to not just detect DR early and prevent consequent vision loss but may also have a role in risk-stratification of patients in terms of renal and CV outcomes. Such an approach could not only improve patient outcomes but could also improve the efficiency and cost-effectiveness of healthcare.
is evidence provides strong support to build prediction models that can ascertain an individual's risk of ESKD, based on fundus examination. Over the last few years, there have been major breakthroughs in automated and semiautomated retinal analysis systems using artificial intelligence (AI) [45]. Although their large-scale use is yet to become a reality, AI prediction models for DKD progression could soon become an integral part of a digital health management platform; some institutions are working on such AI prediction models which could ease the burden of healthcare workers and revolutionize the field of medicine [45,46].
To the best of our knowledge, this is the first metaanalysis to formally evaluate this association of DR and DKD progression. Although the consistency of the association across different measures of effect and sensitivity analyses indicates credibility of our findings, our meta-analysis is limited by the small number of relevant studies that were obtained in the systematic review and the considerable heterogeneity between the studies. Most of the included studies were retrospective and thus carry a risk of confounding. Likewise, in most of the studies, diagnosis of DKD was presumptive and not biopsy-proven. A majority of the included studies reported association of DR and DKD progression risk in type 2 DM and so it is unclear whether the findings of this meta-analysis can be extrapolated to patients with type 1 DM.

Conclusion
Our meta-analysis found that DR is a strong predictor of determining progression of CKD in patients with DKD. is suggests that screening for retinal vascular changes could potentially help in prognostication and risk-stratification of patients with DKD. e severity of DR also can predict progression of DKD. Well-conducted large prospective studies are needed to confirm the findings of this study. Disclosure e sponsor was involved in the design and conduct of the study; collection, management, analysis, interpretation of the data; preparation and review of the manuscript; and the decision to publish. e statistical analysis in this study was undertaken by a consultant biostatistician, Dr. JG. e fees for the biostatistician were paid to her institution by Carl Zeiss India Pvt. Ltd.